| /packages/modules/NeuralNetworks/runtime/test/generated/spec_V1_2/ |
| D | quantize.example.cpp | 7 namespace generated_tests::quantize { namespace
54 namespace generated_tests::quantize { namespace
135 namespace generated_tests::quantize { namespace
182 namespace generated_tests::quantize { namespace
263 namespace generated_tests::quantize { namespace
310 namespace generated_tests::quantize { namespace
391 namespace generated_tests::quantize { namespace
438 namespace generated_tests::quantize { namespace
519 namespace generated_tests::quantize { namespace
566 namespace generated_tests::quantize { namespace
[all …]
|
| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| D | while_sum_of_powers_quant8.mod.py | 35 def quantize(data, scale, offset): function
88 zero = Parameter("zero", DataType10, quantize([0, 0], 1.0, 128))
104 sum_init = Parameter("sum_init", DataType10, quantize([1, 1], 1.0, 128))
109 x: quantize(x_data, 0.5, 128),
111 sum: quantize(sum_data, 1.0, 128),
|
| D | while_sum_of_powers_quant8_signed.mod.py | 35 def quantize(data, scale, offset): function
88 zero = Parameter("zero", DataType10, quantize([0, 0], 1.0, 12))
104 sum_init = Parameter("sum_init", DataType10, quantize([1, 1], 1.0, 12))
109 x: quantize(x_data, 0.5, 12),
111 sum: quantize(sum_data, 1.0, 12),
|
| D | tanh_quant8_signed.mod.py | 24 def quantize(x): function
32 output_values = [quantize(math.tanh(dequantize(x))) for x in input_values]
|
| D | sub_quant8_signed.mod.py | 23 def quantize(x, scale, offset): function
32 return quantize(a_dequantized - b_dequantized, output_scale, output_offset)
|
| /packages/modules/NeuralNetworks/common/operations/ |
| D | Quantize.cpp | 29 namespace quantize { namespace
127 NN_REGISTER_OPERATION(QUANTIZE, "QUANTIZE", quantize::validate, quantize::prepare,
128 quantize::execute, .allowZeroSizedInput = true);
|
| /packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
| D | sub_quantized_different_scales.mod.py | 22 def quantize(x, scale, offset): function
31 return quantize(a_dequantized - b_dequantized, output_scale, output_offset)
|
| D | tanh_v1_2.mod.py | 38 def quantize(x): function
46 output_values = [quantize(math.tanh(dequantize(x))) for x in input_values]
|
| /packages/modules/NeuralNetworks/common/ |
| D | OperationsUtils.cpp | 53 auto quantize = [scale, zero_point](float f) { in CalculateActivationRangeImpl() local
58 *act_min = std::max(qmin, quantize(0.0)); in CalculateActivationRangeImpl()
61 *act_min = std::max(qmin, quantize(0.0)); in CalculateActivationRangeImpl()
62 *act_max = std::min(qmax, quantize(6.0)); in CalculateActivationRangeImpl()
64 *act_min = std::max(qmin, quantize(-1.0)); in CalculateActivationRangeImpl()
65 *act_max = std::min(qmax, quantize(1.0)); in CalculateActivationRangeImpl()
|
| /packages/inputmethods/LatinIME/dictionaries/ |
| D | en_US_wordlist.combined.gz | |
| D | en_wordlist.combined.gz | 1dictionary=main:en,locale=en,description=English,date=1414726273, ... |